Rapid, Multi-Modal Characterization Tools for PV Material Screening and Optimization

Anthony Troupe1, Brandon Motes1, Amy Louks2,3, Axel Palmstrom3, Joseph J. Berry3,4, Dane W. deQuilettes1 1Optigon, Inc., Somerville, MA, United States /2Department of Materials Science, Colorado School of Mines, Golden, CO, United States /3National Renewable Energy Laboratory, Golden, CO, United States /4Department of Physics and Renewable and Sustainable Energy Institute, University of Colorado Boulder , Boulder, CO, United States

Emerging photovoltaic (PV) materials have the potential to add significant value to the PV supply chain, enabling cheap tandem modules, facile manufacturing, and novel form factors. Metrology tools have been critical to the development of PV materials, but current tools are limited in measurement acquisition speeds and difficulty in relating process parameters to material properties. This has hindered the rate of feedback in the research setting and the application of measurement tools on the production line. To fill this gap, we develop an automated metrology tool for photovoltaic materials that takes a series of critical optical measurements at high-throughput manufacturing speeds.  We demonstrate a compact integrated tool with measurement speeds on the millisecond scale for transmission, time-resolved photoluminescence (TRPL), and spectrally-resolved photoluminescence (SRPL). As a demonstration of this tool, we measure 20 half-complete perovskite devices, each with 6 pixels (120 total devices) prepared with different processing recipes. Transmission, TRPL, and SRPL were measured on each pixel area before the devices were complete, for a total of 360 unique measurements. After measurements, the devices were completed in order to correlate optical measurements with device performance. This tool enables the generation of a large data set enabling new directions in data science and machine learning to screen new device layers and optimize device stacks.